Real-Time Surveillance of Rail Integrity by the Deployed Telecom Fiber Infrastructure

Optical fiber sensors based on an interferometric approach appear attractive for an extensive application of optical sensing in the pervasive fiber infrastructure, already deployed for telecommunications purposes. In this article, we show the performance of a sensing system based on Michelson interferometer, exploiting a 48-fiber telecom cable in a conduit under the sidewalk running alongside 4-km railroad tracks, installed by an Italian provider in the north side of Lombardia in Italy. The proposed interferometric scheme does not require an isolated reference, taking advantage of the geometrical arrangement of the sensing and reference fibers inside the same cable to cancel the strong common mode noise, accumulated in the railway hostile environment. Due to the installed sensing system, we monitor the traffic, identifying in a very simple way the passage of trains and the presence of cars at the railroad crossings along the railway. Moreover, we trigger events potentially dangerous for the railway, such as the fall of heavy rocks from the walls along the rail tracks. Due to an appropriate combination of features, we achieve an effective and robust real-time event classification by a supervised artificial neural network (NN), able to recognize the rockfall as a dangerous event for the railway integrity, and provide a prompt alarm, minimizing the nuisance false alarms due to the environment. The proposed sensing system embedded in the telecom network provides a sustainable solution, in terms of cost, energy efficiency, and reliability, without the necessity of coherent detection, high-speed sampling, and complex digital signal processing.